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Safe marginal time of crude oil price via escape problem of econophysics

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  • Li, Jiang-Cheng
  • Leng, Na
  • Zhong, Guang-Yan
  • Wei, Yu
  • Peng, Jia-Sheng

Abstract

Market timing for determining the trading time point and the measurement and prediction of safe holding time is of great theoretical significance and practical value in risk management. Based on statistical physics and escape problems, we put forward the safe marginal time to depict the trading safe area and holding time size, and the theoretical method for risk management is given. Combining with the NYMEX crude oil price index, we make a comparative study between the theoretical and real results of the safe marginal time series. Then we further discuss the predictability of the safe marginal time series through the method of information entropy. The results indicate: (1) the characteristics of safe marginal time is an exponential distribution; (2) the marginal time of safety is positively correlated with price return and negatively correlated with risk; (3) there is an optimal critical initial return that maximizes the expectation and variance of the safe marginal time. In addition, the predictability of safe marginal time has a nonlinear relationship with transaction conditions, and there are some optimal trading conditions that greatly enhances the predictability of safe marginal time. This study provides a method to deal with time series and measure risks from the perspective of safe marginal time. It can provide a reference for investors to measure and predict risks and provide early warning from the perspective of safe marginal time for risk management.

Suggested Citation

  • Li, Jiang-Cheng & Leng, Na & Zhong, Guang-Yan & Wei, Yu & Peng, Jia-Sheng, 2020. "Safe marginal time of crude oil price via escape problem of econophysics," Chaos, Solitons & Fractals, Elsevier, vol. 133(C).
    • Handle: RePEc:eee:chsofr:v:133:y:2020:i:c:s096007792030059x
    DOI: 10.1016/j.chaos.2020.109660
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    as
    1. Charles, Amélie & Darné, Olivier, 2009. "The efficiency of the crude oil markets: Evidence from variance ratio tests," Energy Policy, Elsevier, vol. 37(11), pages 4267-4272, November.
    2. Davide Valenti & Giorgio Fazio & Bernardo Spagnolo, 2017. "The stabilizing effect of volatility in financial markets," Papers 1708.08695, arXiv.org.
    3. Zhong, Guang-Yan & Li, Hai-Feng & Li, Jiang-Cheng & Mei, Dong-Cheng & Tang, Nian-Sheng & Long, Chao, 2019. "Coherence and anti-coherence resonance of corporation finance," Chaos, Solitons & Fractals, Elsevier, vol. 118(C), pages 376-385.
    4. Li, Jiang-Cheng & Tang, Nian-Sheng & Mei, Dong-Cheng & Li, Yun-Xian & Zhang, Wan, 2016. "The trading time risks of stock investment in stock price drop," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 778-787.
    5. Ibrahim A. Onour, 2012. "Crude oil price and stock markets in major oil-exporting countries: evidence of decoupling feature," International Journal of Monetary Economics and Finance, Inderscience Enterprises Ltd, vol. 5(1), pages 1-10.
    6. Zapart, Christopher A., 2009. "On entropy, financial markets and minority games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(7), pages 1157-1172.
    7. Benedetto, F. & Giunta, G. & Mastroeni, L., 2016. "On the predictability of energy commodity markets by an entropy-based computational method," Energy Economics, Elsevier, vol. 54(C), pages 302-312.
    8. Graham Elliott & Allan Timmermann, 2016. "Forecasting in Economics and Finance," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 81-110, October.
    9. Banerjee, Shantanu & Güçbilmez, Ufuk & Pawlina, Grzegorz, 2014. "Optimal exercise of jointly held real options: A Nash bargaining approach with value diversion," European Journal of Operational Research, Elsevier, vol. 239(2), pages 565-578.
    10. Shahrzad Faghih-Roohi & Yew-Soon Ong & Sobhan Asian & Allan N. Zhang, 2016. "Dynamic conditional value-at-risk model for routing and scheduling of hazardous material transportation networks," Annals of Operations Research, Springer, vol. 247(2), pages 715-734, December.
    11. Yue-Hua Dai & Wen-Jie Xie & Zhi-Qiang Jiang & George J. Jiang & Wei-Xing Zhou, 2016. "Correlation structure and principal components in the global crude oil market," Empirical Economics, Springer, vol. 51(4), pages 1501-1519, December.
    12. Miller, J. Isaac & Ratti, Ronald A., 2009. "Crude oil and stock markets: Stability, instability, and bubbles," Energy Economics, Elsevier, vol. 31(4), pages 559-568, July.
    13. W. M. Patefield, 1981. "An Efficient Method of Generating Random R × C Tables with Given Row and Column Totals," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 30(1), pages 91-97, March.
    14. Decamps, Jean-Paul & Mariotti, Thomas, 2004. "Investment timing and learning externalities," Journal of Economic Theory, Elsevier, vol. 118(1), pages 80-102, September.
    15. Wang, Minggang & Chen, Ying & Tian, Lixin & Jiang, Shumin & Tian, Zihao & Du, Ruijin, 2016. "Fluctuation behavior analysis of international crude oil and gasoline price based on complex network perspective," Applied Energy, Elsevier, vol. 175(C), pages 109-127.
    16. Zhong, Guang-Yan & Li, Jiang-Cheng & Jiang, George J. & Li, Hai-Feng & Tao, Hui-Ming, 2018. "The time delay restraining the herd behavior with Bayesian approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 335-346.
    17. Fleten, Stein-Erik & Linnerud, Kristin & Molnár, Peter & Tandberg Nygaard, Maria, 2016. "Green electricity investment timing in practice: Real options or net present value?," Energy, Elsevier, vol. 116(P1), pages 498-506.
    18. Barucca, Paolo & Lillo, Fabrizio, 2016. "Disentangling bipartite and core-periphery structure in financial networks," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 244-253.
    19. Mallick, Hrushikesh & Mahalik, Mantu Kumar & Sahoo, Manoranjan, 2018. "Is crude oil price detrimental to domestic private investment for an emerging economy? The role of public sector investment and financial sector development in an era of globalization," Energy Economics, Elsevier, vol. 69(C), pages 307-324.
    20. Bøckman, Thor & Fleten, Stein-Erik & Juliussen, Erik & Langhammer, Håvard J. & Revdal, Ingemar, 2008. "Investment timing and optimal capacity choice for small hydropower projects," European Journal of Operational Research, Elsevier, vol. 190(1), pages 255-267, October.
    21. Muhammad Ishfaq Ahmad & Wang Guohui & Muhammad Yasir Rafiq & Mudassar Hasan & Ata-Ul-Haq Chohan & Anika Sattar, 2017. "Assesing Performance of Moving Average Investment Timing Strategy Over the UK Stock Market," Journal of Developing Areas, Tennessee State University, College of Business, vol. 51(3), pages 349-362, July-Sept.
    22. Maasoumi, Esfandiar & Racine, Jeff, 2002. "Entropy and predictability of stock market returns," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 291-312, March.
    23. Safar Fazli & Reza Kiani & Mohammadali Vosooghidizaji, 2015. "Crude oil supply chain risk management with DEMATEL–ANP," Post-Print hal-02327343, HAL.
    24. Wang, Yudong & Ma, Feng & Wei, Yu & Wu, Chongfeng, 2016. "Forecasting realized volatility in a changing world: A dynamic model averaging approach," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 136-149.
    25. Delaney, Laura, 2018. "Investment in high-frequency trading technology: A real options approach," European Journal of Operational Research, Elsevier, vol. 270(1), pages 375-385.
    26. Li, Bingxin, 2018. "Speculation, risk aversion, and risk premiums in the crude oil market," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 64-81.
    27. Liu, Xiaojia & An, Haizhong & Wang, Lijun & Guan, Qing, 2017. "Quantified moving average strategy of crude oil futures market based on fuzzy logic rules and genetic algorithms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 444-457.
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